0:00

AI is in such an early stage

0:02

that the next five , 10 years are really

0:04

going to tell us what that industry is going

0:06

to look like . The more AI literacy

0:08

that you can build up today , the better . I

0:10

think the best way to do that is by following

0:13

your passions , your hobbies . You said you were working

0:15

with mid-journey . If you're an artist

0:17

, if you like to draw , if you like creating art , then

0:19

I think mid-journey is such a great tool to

0:21

start playing around with your own art and also

0:24

seeing how it responds to art . I

0:26

think AI literacy in order to develop

0:28

that the best way to do it is to figure out what are your hobbies

0:30

, what are your passions . If you like writing

0:32

, play around with chat to BT or other large

0:35

language models . If you like composing

0:37

music , or if you like paying music , play around with

0:39

an AI tool in the music scene and understand

0:42

how to prompt it , how to use it to create something

0:44

new . Because I think as you learn

0:46

those skills , you'll be able to become

0:48

an expert , because anyone today

0:50

can become an expert in AI because it's just so

0:53

new , so early , and the more time

0:55

you invest in it today , the better you'll

0:57

be . And the best way to invest time is by doing

0:59

it through a hobby or something that you're passionate

1:01

about .

1:02

Hello and welcome to Developers'

1:04

Journey , the podcast bringing you the making

1:06

of stories of successful software

1:08

developers to help you on your

1:11

upcoming journey . I'm your host , tim

1:13

Bologna . On this episode , I

1:15

receive Denzil Aden . As

1:18

a solo technical founder , denzil

1:20

carved her niche with

1:22

an AI-focused degree from MIT , mba

1:25

from Harvard and a distinguished

1:27

career at Microsoft . Wow

1:29

. She is devoted to making your life

1:32

smarter with AI , enhancing routines

1:34

, automating mundane tasks oh , I

1:36

love that one and maximizing every minute

1:38

of your day . Don't

1:40

love that one that much . As

1:43

with Smartie , and only in

1:45

one AI productivity assistant

1:47

. She builds , and when she unplugs because

1:49

she does sometimes Denzil

1:52

plays the piano , offers fiction

1:54

and upheads and subs tea

1:56

. That's a program

1:58

, denzil . Welcome to Dev Journey .

2:00

Thank you so much for having me . I'm excited to be here .

2:03

Oh , I'm excited as well , and it's been so long . We

2:06

scheduled a couple of times I had to reschedule

2:08

, so I'm really thrilled this is happening right now . Let's

2:10

wait Me too , but before we come to your

2:12

story , I want to thank the terrific

2:15

listeners who support the show . Every

2:17

month you are keeping

2:19

the Dev Journey lights up . If you

2:21

would like to join this fine

2:23

crew and help me spend more time

2:25

on finding phenomenal guests

2:27

than editing audio tracks , please

2:30

go to our website , devjourneyinfo

2:32

and click on the support

2:35

me on Patreon button . Even the

2:37

smallest contributions are giant

2:39

steps toward a sustainable

2:41

Dev Journey journey . Thank

2:44

you , and now back to today's guest

2:46

. So , denzil , as you know , the

2:49

show exists to help the listener understand

2:51

what your story looked like and imagine

2:53

how to shape their own future . So

2:55

, as usual on the show , let's go

2:57

back to your beginnings . Where would you place the

3:00

start of your Dev Journey ?

3:02

That's a great question and I

3:04

love the start of my Dev Journey because it started

3:06

very young . I was eight years old

3:08

, I was in third

3:10

grade and we had just taken our

3:12

first computer class where we

3:14

learned about logo . And I don't know if you're familiar

3:17

with logo , but it's this children's

3:19

programming language with a little turtle and

3:21

you tell the turtle where to go , what to do

3:23

to build a house , and

3:25

I fell in love . That's when I first

3:27

started programming . It's actually logo is like the

3:29

first time I used recursion

3:32

. It was the first time I learned how to make

3:34

if this , then that statements and I

3:36

fell in love and I clicked instantly

3:39

for me . I just understood

3:41

how to talk to this turtle

3:43

and I could tell that

3:45

my friends didn't get it as well

3:47

as I did and it just felt

3:50

very magical and I'm lucky . I grew

3:52

up in a very tech

3:54

area of California . I was in the Silicon Valley

3:56

, my dad was an electrical

3:59

engineer and a software engineer , and so I had

4:01

some exposure to that early on , but I

4:03

never thought of myself as a software engineer . That

4:06

was something that I even wanted to do until

4:08

I started playing around with logo and

4:10

it just opened up all of these doors for me and

4:13

I started coding because of that very

4:15

young . I took that passion with me through

4:17

high school to eventually

4:19

went to college at MIT and I

4:21

chose to go there because I really wanted to study

4:23

computer science , although I was still very

4:25

convinced that I didn't want to be a software engineer . I

4:27

wanted to do something else with technology . So I tried

4:30

biotech . I tried out a bunch

4:32

of different careers but I kept coming back to

4:34

just pure building and

4:36

I ended up doing a master's at

4:38

MIT as well . My master's had a theoretical

4:40

focus in AI , but

4:42

I did a thesis project in human

4:44

computer interactions and I ended

4:46

up building pretty much a precursor to Slack

4:49

, but for the classroom . So

4:52

it was a collaborative , asynchronous platform

4:54

, but for education

4:56

classrooms , and that's what I wrote my thesis on . It

4:59

was something that I wish I had stuck with , but

5:01

I really didn't think I could be a founder . I

5:03

thought that being a founder wasn't for me and

5:06

I wasn't really sure who the profile was . But it wasn't something that

5:08

I wanted to pursue . So I

5:10

ended up going to big tech instead . I

5:12

started as a PM at PowerPoint

5:15

, liked it but missed coding . So

5:17

I started teaching computer science at a

5:19

community college and then eventually at

5:21

San Francisco State , just as a guest lecturer . And

5:24

then I still missed coding and

5:27

so then ended up switching to being a software

5:29

engineer at Yammer . But I've always

5:31

been in the enterprise productivity space , always

5:33

in the future of work tools and helping people

5:35

be more productive at work , specifically

5:37

at Microsoft . But even during

5:40

that time I wasn't sure exactly what I wanted to do

5:42

. I wasn't sure if that was

5:44

what I should focus on for the rest of my life . So I started trying

5:46

out a bunch of different careers , from

5:48

law , from finance to politics , decided

5:51

to go to business school and really both broadened

5:53

my skill set but

5:56

also give me some time to figure out what

5:58

is it that I want to do with this time and

6:01

with my passion and my curiosities ? And

6:03

that's really where I came up with the idea for Smurdy . I

6:06

almost reverse engineered into it . I was still trying out different

6:08

things , but I asked myself if I could only work on

6:10

one thing for the rest of my life . What would

6:12

it be ? And this was back in 2018 . And

6:15

AI was interesting

6:17

, but it wasn't like it is today . And

6:19

it's funny . I used the same pitch for my startup , smurdy

6:21

, today that I did in 2018 , but

6:24

the appetite for it has changed so drastically

6:26

. But back then I was like , if

6:28

I do believe this future is coming and

6:31

I want to be part of that future . And so I started really

6:33

building Smurdy for myself , reverse

6:36

engineered into what the product

6:38

is today and tried to raise money in business

6:40

school . It didn't work out and

6:43

then I kept pitching to the same people . I

6:45

kept iterating my pitch , kept iterating the product and

6:48

eventually raised that first check which

6:50

made it easier to raise more money , and now

6:52

I'm working on it full time .

6:54

And congratulations on that . Thanks , but

6:57

that's a whole bunch to unpack before

7:00

we get to Smurdy . That's okay for you ? Yes , definitely

7:02

. I'd

7:04

like to come back to that turtle , the way

7:06

you talked about it , saying

7:09

well , I understood how to talk to that turtle . I love this formulation

7:12

Because that's really something . When

7:14

you're trying to talk to a computer and

7:17

trying to tell it to do something and you're not speaking

7:19

the right language , it doesn't click . As you

7:21

said , it's so

7:24

difficult to really Understand

7:27

the way you should be talking to it and the way

7:29

you personally find this turtle or this computer

7:31

as a total and say I understood how to talk

7:33

to it . I love it . It's really saying , hey

7:35

, you found the right language . Did

7:38

you realize right away the

7:40

power that software could

7:42

have and so what the

7:44

power you had learned in talking to that turtle

7:46

could bring to your life ? Not

7:49

yet at that point .

7:51

I don't know if at that point I understood how

7:53

transformative of a technology any

7:55

sort of software language , programming language is

7:58

, but I did understand that computers

8:00

spoke differently than humans did

8:02

, and that's what programming languages allowed

8:04

us to do , that they allowed us to communicate what

8:06

we wanted To

8:08

technology , and I actually think the greatest

8:11

thing about a I today is that

8:13

it's made it even easier for humans to communicate

8:15

with technology , because now technology can communicate

8:17

the way we communicate . But back then we

8:19

needed to learn how to use these

8:21

intermediary bridge languages in

8:23

order to be able to allow

8:26

software to do what we wanted , and

8:28

I thought that was really fascinating . I was always really

8:30

into logic and puzzles , and it was

8:32

just a puzzle that needed to be solved , and

8:35

then , as I grew older , I really

8:37

understood OK , like these are

8:39

the limits of technology , this is what are

8:41

the limits of my own programming skills , and try

8:43

to find connections there .

8:47

How is has been your , your

8:50

relationship with

8:52

students ? You mentioned you were a teacher for a bit

8:54

with students for whom it

8:56

didn't click the way you did for you and

8:58

and bridging that gap and helping

9:01

them understand exactly how

9:03

that work . If it clicked for you from

9:06

the get go love at first sight I would almost

9:08

say how did you bridge that gap and build this relation with students

9:10

?

9:11

That's a great question , and teaching was

9:13

like such a great experience for me because it really showed

9:16

me that everyone just learns in a different way

9:18

. No skill is unknowable . It

9:20

is just about finding the way that your

9:22

brain works , your thinking patterns

9:25

work , and trying to find alignment . And so

9:27

, for me , I really gave me

9:29

a great perspective on what is wrong with education

9:31

today , and also

9:33

that no one can say

9:36

that they're not a coder because you have the skills

9:38

, you have the ability to think . It's just

9:40

about figuring out how to make your

9:42

brain talk , the way that computer brains talk .

9:46

So do you have some , some , some techniques

9:49

, when it's not clicking , with people

9:51

to find the way that they need

9:53

to hear it , so that clicks ?

9:56

I don't know if it's necessarily about like how you

9:59

hear it , but I will say it is about practice , because

10:01

the more you do different

10:03

exercises , you'll start to recognize patterns

10:05

between how you solve certain problems

10:08

in the computer science space and

10:11

Java , and you'll find

10:13

the most problems that you're seeing in the

10:15

classroom setting are just variations of

10:17

the same same conundrum

10:19

. And then you just need to start recognizing

10:22

OK , like this is how these are the parameters

10:24

that the function needs . This is how functions

10:26

are usually structured , and so I think it's practice

10:29

more than anything else , practicing to think

10:31

the way that computers think and learning what

10:33

they need .

10:35

OK , so really using it , using it , using

10:37

it , and at some point you will

10:39

see and it will click .

10:41

Exactly , and I think that's true today

10:43

too , with all of these tools that are out

10:45

there and all of this , all

10:48

of the hype around prompt engineering . It is about

10:50

practicing learning how to prompt

10:52

these models . It's learning about

10:54

how AI models think

10:56

and understanding how you can , like , adapt

10:59

your own thinking to match that .

11:02

Isn't there a difference though , in

11:05

such that a programming language is

11:08

is very , very

11:11

Cartesian and definite . Either you

11:13

have the right way to ask or you don't , and there's no

11:15

two ways on all of those

11:18

, no three ways to do the same thing . In a way

11:20

, crafting

11:23

your prompts with chad , gpt

11:25

or with the LMS we have nowadays

11:27

, you can achieve the same results with

11:30

very different ways , and so dabbling into

11:32

it quite often leads to some

11:34

results as well , and it's not a black and

11:36

white result . It's very shades of gray , except

11:39

if you add some parameters etc . But but

11:41

if you stick to the , to the prompting

11:44

, it's really shades of gray . Harder

11:47

in computer science to double your

11:50

way into the , how the computer is supposed

11:52

to , to be talked to .

11:54

I think that's a great point . I agree with you . Like with

11:57

a traditional programming language

11:59

, there is only one right way to

12:01

talk to software

12:03

, to whatever you're trying to get

12:05

done with prompt engineering . Of course , you can

12:08

ask something in multiple ways and you'll get different

12:10

results , and you should probably experiment so you can

12:12

see what parameters lead to what results

12:14

. But at the same time , I do believe

12:16

that there's like an optimal way to

12:19

do prompting , and we just haven't fully

12:21

discovered that yet . I think five years from

12:23

now there will be textbooks that will say like this

12:25

is exactly how you should be prompting this model

12:28

specifically , and I think that

12:30

precision will come . But

12:32

right now we're all in this exploratory

12:34

phase , trying

12:36

to understand what is the best language .

12:40

Oh , we are still a baby phase

12:42

of asking questions . I'm

12:45

exploring a lot of mid journey

12:47

in the past days and weeks

12:49

and understanding

12:51

some patterns and how to have to ask questions

12:53

. This is , this is fantastic

12:56

. This is an endeavor in itself and

12:58

indeed , when you find something that really works

13:00

and you can reproduce and is really consistency

13:02

, oh , now I really learned something

13:04

. That's

13:06

very gratifying .

13:08

I agree it's an adventure and it's really fun .

13:12

It is so . You

13:15

said obviously MIT , obviously

13:17

computer science , even though you don't want to become

13:19

a hardcore software engineer

13:22

, you said but but still

13:24

it had to be in SIFT3 engineer . Did

13:27

you have doubts in which direction

13:29

to take inside

13:31

the CS space ?

13:34

No , I was always interested in

13:36

AI , so I knew that I wanted to do my theoretical

13:38

masters in that , and then I

13:40

always knew I wanted to pursue

13:42

computer science . There was no other major

13:45

that appealed to me . I just

13:47

wasn't sure what I wanted to do with that major

13:49

, and so that was what was most confusing

13:52

for me . And then , in terms of choosing

13:54

which university go to , I actually wasn't

13:57

sure I wanted to go to MIT , and

13:59

then I visited during their

14:01

campus preview weekend , which happens in

14:03

April , and it was the most

14:06

fun weekend I had ever had in my

14:08

life up until that point , and

14:10

it convinced me that this was the right place

14:12

for me to go to . And so

14:14

it all really just fell into place

14:16

, and I just needed to experience it once to

14:18

know it was the right fit .

14:20

Okay , was that weekend representative

14:23

for the years you did after ?

14:26

Yes , actually , it really was .

14:27

Okay .

14:29

It was very so . I think MIT has this motto

14:31

, which is work hard , play hard , and even that

14:33

weekend was very much like

14:35

extremely intense

14:37

but very fun at the same time , and

14:40

I think it just it does a really good job

14:42

of showing you what your college experience

14:44

could be like . It's all student run

14:46

. Obviously , there's like administration overseeing

14:49

everything , but students really plan

14:51

all of their events and it's just 24

14:54

seven for three days . Okay

14:56

, and the rest of the curriculum

14:58

is 24 seven for four years , five

15:00

years , but it's a little

15:02

bit less recreational

15:05

only , but I mean even , but it's the same

15:07

level of intensity .

15:08

Okay , that's good , that's good . It's really

15:10

a hard or a very thin line to

15:13

to meet during

15:15

those open doors to really show

15:17

the the values and what

15:19

the school is made or the college is made

15:21

of , and then have

15:23

the same feeling afterwards and not feel

15:26

lied

15:28

to . It's really hard , it's

15:30

a very hard balance .

15:31

I personally I'm obviously biased , but

15:33

I thought MIT did a really great job and I actually

15:35

went with a friend of mine from high school

15:38

. We both went and she did not have

15:40

as good of an experience and she did not end up going

15:42

to MIT and so I think it

15:44

does do a good job for prospective

15:46

students to come see what the atmosphere

15:49

is like , see what the culture is like , and then have them decide

15:51

like is this for you or not ?

15:53

Yeah , indeed , indeed , indeed . Then

15:55

, moving on , when you spoke about your theoretical

15:57

stereotypical thesis , you

16:00

just said I wish I'd stayed with

16:02

this topic . What

16:05

do you mean by that ?

16:06

Yeah , so it's actually not with . So

16:08

the way that my master's was broken

16:10

down I could take classes

16:12

and concentrated in a space and then

16:14

I could do a thesis project in

16:18

any space that I wanted , ideally

16:20

with complementary skills

16:22

to my theoretical thesis . Well , my theoretical concentration

16:24

wasn't AI , but back then it was . Machine

16:26

learning was there , but it was still early

16:29

. I didn't really like pursue that as much . I

16:31

was still doing more of like a high level

16:33

. AI 101 theoretical concentration

16:35

and then my application

16:37

thesis project was in human

16:40

computer interactions and I built this

16:42

platform called Nora no one revises

16:44

alone and it was literally

16:47

slack , but for classrooms and

16:49

it was for helping students asynchronously

16:52

collaborate on assignments during

16:55

the school day , and I , in

16:58

hindsight and even then , could have turned

17:00

it into an actual product and business

17:02

, but I didn't do it and

17:05

I don't know why . I

17:07

just felt very I guess I was very afraid of the idea of

17:10

striking out on my own and

17:12

building a company with a product that I

17:14

already had , with users who were

17:16

willing to pay for it , and I

17:19

think it was just . It was a different time really , because I feel like

17:22

universities today have a lot

17:24

more programs

17:26

around entrepreneurship and MIT than

17:28

did , but it wasn't a

17:31

big part of the campus culture and if

17:33

I go to campus now , it's so different . There are so many

17:36

programs around . How do you start a startup , how do you raise

17:38

money , how do you start building

17:40

something people want , and

17:43

so that's really what I meant . I had this thing that I really

17:45

, even in hindsight now , could

17:47

have created a real company around , but it was

17:49

just so hard for me to grasp that

17:52

that was something I could do and that this was enough

17:54

of a starting point to get started .

17:57

Okay , makes more sense . So you were not ready

17:59

for the startup growing experience yet

18:01

, yeah , okay

18:04

, and does this product

18:07

still has its place in the

18:09

world 10 years later ? No , timing

18:11

is everything .

18:12

And even then it was a

18:14

little bit too early for that

18:16

asynchronous collaboration

18:19

platform , but I definitely think

18:21

there was still a lot of value that it was adding , especially

18:25

in the classroom setting . But today there's so many alternatives there's Slack , there's

18:27

Miro , there's so many different platforms that you can use to

18:29

get that same experience . Honestly

18:33

, figma could even replace what I built , and

18:35

so I think it had its time . But that's time that

18:39

time has passed Okay , so

18:41

no regrets .

18:42

No regrets so then you brushed over your your

18:44

first years

18:48

PM at PowerPoint

18:50

, then think , yemmer . Then there

18:52

was one in between . I think how long did that

18:55

phase last ? Or

18:58

go until you had this

19:00

reboot of saying what do I want to do with my life ?

19:03

Yeah , I was working for three

19:05

years a little bit more than that and then I decided to go to business

19:09

school and business school was really that period of reflection .

19:13

So how did you three years go ? I

19:16

mean starting the three years entering the , the workforce

19:18

with big

19:20

air quotes or industry or big

19:22

tech , as you mentioned it . How did that go ? How did it relate to

19:26

the ideal you had

19:28

in your mind ? How did that work ? And then , how do these three years

19:30

evolve into you questioning this and say , well

19:32

, maybe I should go back to business school

19:35

or whatever . I'm very interested

19:37

in those two . To pals yeah , no , it's a great question

19:39

because I don't think that enough people talk about , like what

19:41

that

19:45

feels like when you first go into the workforce .

19:47

It was jarring for me . It was not what I

19:51

expected . I wasn't sure if I

19:53

loved my job and I didn't know why . And it turns out that

19:55

I really did like my job . I was just hungry

19:57

for more and I just felt I wasn't

19:59

being challenged enough . I didn't

20:02

love my commute , which is so funny now to talk

20:04

about , but my commute was terrible back then

20:07

. It was an hour because I lived in San Francisco

20:09

. I wanted the lifestyle of being young and happy with my friends all the time

20:11

, but then I was commuting to Mountain View

20:13

and with

20:18

traffic that would take an hour each way , I just

20:22

felt surprised at what

20:24

I did like and also surprised at what I didn't

20:26

like . I didn't realize how important the lifestyle

20:28

aspect would be to me . I didn't realize how

20:30

much I would miss coding and actually building something from

20:36

like specifications versus writing the specifications

20:38

, and I didn't understand how different

20:42

those skill sets were . I didn't really understand at that

20:44

time how in front of was to understand users and

20:46

be customer obsessed , even though I was working in product

20:48

and it was . I

20:50

was learning so much but at the same time not appreciating

20:53

what I was learning , and so it's funny

20:57

to look at it with hindsight . And then , because I missed coding so much , I started

20:59

teaching

21:02

computer science and I realized

21:05

that I liked teaching , but it wasn't something that I wanted

21:07

to do as my full-time livelihood , so I didn't

21:09

want to go back to school to become a professor

21:14

and so I started looking at other jobs

21:16

and I think my number one priority at that time had

21:21

been finding something that

21:23

was in San Francisco . So that was my number one priority . And

21:25

then I

21:28

was lucky enough to interview at Yammer , which was a acquired

21:30

startup at Microsoft and their headquarters was in

21:32

San Francisco . So that worked out really well

21:35

on that specification and they were looking for software

21:37

engineers . So it worked out in that way

21:39

and I still got to stand at the Microsoft

21:43

umbrella , so it was an easy transition and

21:45

so it worked out so well for everything that I thought I wanted at that

21:47

time . So I switched to being a software engineer at Yammer

21:49

and I actually really

21:53

liked it . I liked being the one building

21:55

and seeing my changes get deployed

21:57

into the product

22:00

and seeing how users use them . It was just such

22:02

a satisfying feeling . So I was like , okay , I

22:04

do like this part of it . But

22:06

then , a year into that , I

22:10

ran into that same feeling of like okay

22:12

, but I want more . I want more challenges , I want

22:14

more to do . I don't know if this is

22:16

where I want to be for the next five or 10

22:18

years . I

22:20

just felt really hungry

22:23

but also really lost . That's

22:25

why I decided that business school was the right choice for

22:27

me . But it's so funny I remember

22:29

even now , when I decided to go to business school

22:31

, the head of engineering at Yammer , who I like never

22:34

worked with but I knew of , sat

22:36

me down and said okay , I

22:38

see how hungry you are , I see that you're

22:40

like pursuing other things and I don't

22:43

think you need to stay at Yammer . This is not a pitch

22:45

for you to stay at Yammer . I can help

22:47

you work at any startup that you want

22:49

, any place where you can like build the skill

22:51

set , but I feel like you should really go and

22:53

build instead . That was the first time anyone had

22:55

said to me like going to business school was the wrong

22:57

choice , and I

23:00

really look back on it today very fondly

23:03

because I understand what he was trying to say . He was saying

23:05

there are so many ways to get the same

23:07

skill set and to feed

23:10

that passion of wanting to build and learn

23:12

at an accelerated rate . I

23:16

think it really stuck with me about wanting

23:18

to go to a different startup , like starting a startup going

23:20

somewhere younger and smaller . I

23:23

think I just thought about that a lot while I was at business

23:25

school . That was my experience working

23:28

full-time for the first time .

23:31

It makes a lot of sense . How did

23:33

you come up to the idea of going back

23:36

with their quotes again to business school and

23:38

decide on business school that business

23:40

school was the right thing for you at that time

23:42

?

23:43

That's a great question . I actually applied to a lot

23:46

of different grad schools . I applied to law school , I

23:48

applied to a school for masters

23:50

of public policy . I

23:53

was confused in a

23:55

lot of ways about what I wanted

23:57

. The great thing about tech is that

24:00

it can be applied to any industry . There are

24:02

law tech , there is finance tech

24:04

. There is so many different ways you

24:06

can apply technology to different industries . I

24:08

was like , okay , I can bring this skill set to

24:10

any space and any career that I want

24:12

. I just have to figure out what I want to do . I

24:15

kind of glossed over this , but in my working

24:18

days I was actually interning on

24:21

the side at a lot of other things as well . I

24:23

was working for a Kamala

24:26

Harris Senate campaign . I was volunteering

24:28

for them and helping them with fundraising

24:30

. I was interning with a

24:32

criminal lawyer and trying to understand

24:35

if I wanted to go into criminal law , and this was

24:37

actually my third time trying out

24:39

a law internship . I had already worked in patent

24:41

law . Before that I tried a corporate law

24:43

internship as well . I

24:46

was confused and I was curious

24:49

. I wanted to try a lot of different things

24:51

and figure out what was right

24:53

for me .

24:55

I love the experimental approach

24:57

Really . Okay , I don't know

24:59

what I want , so let's try this , let's

25:02

try that , let's try that , let's try that and see what sticks

25:04

. Very entrepreneurial

25:06

.

25:07

Definitely . It's so funny because I never looked at

25:09

that skill or that the

25:12

mindset as entrepreneurial . But now that

25:14

I look at my life

25:16

in hindsight I can say very clearly

25:18

well , those are entrepreneurial skills . That

25:22

is part of it , that experimental

25:24

learning by doing which is not for everyone . Some

25:26

people are actually really great at looking at other people's

25:29

experiences and other people's mistakes and

25:31

learning from that . I'm not , and I wish

25:33

I was better at that , but I am very much a

25:35

experimenter , trier , iterator

25:38

.

25:40

Which you need nowadays , so that's fine . So

25:43

I've reached the point

25:45

in time where Smarties started to evolve in your

25:47

mind .

25:48

Exactly .

25:49

So can you tell us

25:52

the birth story of Smarties

25:55

before it became the company ? How did

25:57

you come up with the idea ? How did you did

25:59

that ? Maybe scratch an itch you had

26:01

or really started to evolve

26:03

into , from maybe just an

26:05

idea or a hobby into hey

26:08

, this could be more . And

26:10

what the first steps look like .

26:11

Yes , definitely , it's

26:14

very clear in my mind . So

26:16

it happened during my second year of business school

26:18

, maybe a little bit during the first year

26:20

I'd all . I arrived

26:22

at business school , I liked it , I

26:25

was open to trying out other careers

26:28

, and then I kept finding myself coming back to tech

26:30

and I said that I didn't want to pivot out of technology

26:32

and so what can I do with

26:34

technology ? And

26:37

HBS was really the first time I felt supported

26:39

in entrepreneurship and

26:41

pursuing that as a journey . There

26:44

were so many classes around it . I still think HBS

26:46

is very theoretical when it comes to entrepreneurship

26:48

, compared to some other business schools that are , I think , a little

26:50

bit more application heavy , and I

26:53

know they're changing that . They're trying to

26:55

become more application and

26:57

experimental focus , but at the time it was

26:59

still more theoretical , I think . But

27:02

it was my first exposure to that as

27:04

an experience , and one of my closest friends

27:06

at a business school had been a founder before

27:09

, and so I really got to see what that journey had

27:11

been like for him and he wanted to start another

27:13

startup right away , and so

27:15

it was exciting to see the

27:18

world through his eyes and that lens

27:20

and it definitely encouraged me to

27:22

think about that as a career path

27:24

for myself . And so then I started asking myself

27:26

okay , if I could only work on one thing for the rest

27:28

of my life , what space do I want to

27:30

be in ? And AI had always been something

27:32

that I was really excited about . I wanted to help be

27:34

part of that journey of making that a reality

27:37

, and back then it was still very much machine

27:39

learning , natural language processing , nothing

27:41

like what we have today with LLMs

27:44

, but it was still something that was rapidly

27:47

advancing and so I was like I want

27:49

to be in that space , I want to see how I can get

27:51

into that . And then I started asking about questions

27:54

in my own life , problems in my own life , and

27:56

at that time I really vividly remember I

27:59

was having anxiety

28:01

attacks like pretty much every day . I just felt

28:03

so overwhelmed with everything that was in

28:05

my life , both my personal commitments , my

28:07

professional commitments , everything

28:10

that I was trying to balance , and

28:12

I had this realization that

28:14

more than 25%

28:16

of the things that I was doing every day could easily

28:19

be automated with existing technology

28:21

. And I remember looking

28:23

it up and I think a lot of corporate

28:26

knowledge workers at that time had like 30%

28:28

. Today I would say it's about 60%

28:30

of the work that we do every day could easily be automated

28:33

with existing technology , and the big problem

28:35

there and why that wasn't being solved

28:37

with technology , was that none of

28:43

our software was able to talk to each other . We

28:45

had to manually handle every software

28:47

individually . Everything was in these different silos

28:50

, and so I was

28:52

on this kick of OK

28:54

, everything has an API . Apis can talk

28:57

to each other . Apis are programming

28:59

languages . Apis are languages for

29:01

how software speaks to other software , and

29:03

all I needed to do was create this

29:05

hub that allowed these APIs to connect

29:08

, and I should be

29:10

able to talk to this hub , and so that's how Smarty

29:12

really came up as an idea in my

29:14

mind . I had this vision around this

29:16

conversational web operating system

29:18

where I tell Smarty what I need to do , smarty

29:21

figures out the intent , what APIs

29:23

are relevant , and then connects it all together and makes it

29:25

work , and that's

29:28

how I came up with the idea , and

29:30

I started building Smarty as a chat

29:32

bot , just something that I was chatting

29:34

to . I would tell Smarty things that were on my

29:36

plate , and if Smarty could automate it

29:38

, it would , and that's how I got

29:40

started . That's the pitch that I gave

29:43

to my first investor . I

29:45

didn't really understand anything about how

29:47

to pitch , how

29:49

this is too big of an idea and you need a niche

29:51

to get started . You need a real

29:53

pain point , you need a real customer . It was definitely

29:56

a learning journey for me , but

29:58

that's how I got started .

30:00

And it is awesome , it was very long-winded . No

30:04

, no , that's . It's really cool . I was really thinking

30:07

what would be the analogy with existing

30:09

tools . It's kind of an

30:12

overlay over Zapier , which

30:14

has the connectors , but not this AI

30:17

part , where it figures out on

30:19

its own what it should be doing . You

30:21

really have to tell them , but

30:25

it's not just that . So , yeah , interesting

30:27

. And this started in 2018

30:30

, isn't it so

30:32

? Before chatGPT emerged

30:35

, or at least to the public , before

30:38

everybody understood

30:40

that this is happening ? How

30:43

was it to work in LLM back

30:45

then versus now ?

30:47

Yeah , it was a different way of thinking about

30:50

AI . It was very much around I was using

30:52

an open AI API

30:54

for natural language processing , but that isn't

30:57

what chatGPT is today . Then

30:59

I had these goals around creating machine

31:01

learning models , but everything that has happened

31:03

in the last couple of years has completely changed

31:05

that Not just for me , but for people who

31:07

were machine learning experts working at companies

31:10

building these models , it is

31:12

a brave new world , but not

31:14

a surprising one . Even back then , I had

31:16

that same vision that LLMs make even

31:18

easier today , but it's

31:21

just a different methodology to get there .

31:24

Did you change some part of your stack after

31:27

LLMs came out ?

31:34

No , I would call it AI 1.0 . We

31:36

had that before

31:38

and today we're still using that , but now we're layering

31:40

in AI 2.0 with all of the

31:42

language learning models and also large action

31:45

models . Really

31:47

, this is a new

31:49

time for how

31:52

the AI works , but in terms of

31:54

the actual infrastructure that you need to build

31:56

a product like Smarty , all of that stays

31:58

the same the APIs that

32:00

were connected to you , how those APIs connect together

32:03

, how you as

32:05

a user communicate with Smarty and what information

32:08

you need to specify all of that stays the

32:10

same . In some ways , I feel like it

32:12

was great that I had that period of building up that

32:14

infrastructure and now I get to

32:16

just play around with how the AI

32:19

at the top level works for how users

32:21

interface with Smarty .

32:24

Who do you define as your competitors ? Are

32:28

those the Zappiers which

32:30

are trying to add AI on top of

32:32

the services now , or is that a different space

32:34

?

32:35

It's a different space , and so I can

32:37

almost see Zappier or IFTHT IFTHT

32:40

, this and that being APIs that we integrate

32:42

with . It's really not even a

32:44

competitor because they

32:46

are really providing

32:48

the tools from creating these very intricate connections

32:51

, and I can see Smarty even using those

32:53

intricate connections between these different

32:55

APIs . Our competitors are more in the

32:57

future of work tool space , so tools

32:59

that are creating countering solutions , tools

33:01

that are creating email management solutions , contact

33:03

management solutions , and these are tools that

33:05

you're using at work . But

33:08

a lot of our users have product fatigue because

33:10

they don't want to switch between all of these different

33:12

niche productivity tools . They instead

33:15

want an all-in-one platform

33:17

that handles all of their favorite productivity

33:19

features , and so we're more in that

33:22

space , and so I would say Smarty's biggest

33:24

value proposition is first , this all-in-one

33:27

platform , trying to integrate with everything

33:29

across your administrative stack and right now

33:31

we're just on top of G Suite but everything from your

33:33

email to your Google contacts , to your Google

33:36

calendars , across multiple accounts

33:38

. So your professional accounts , your personal accounts

33:40

, just having all of that accessible in one place

33:42

. So that's our top value proposition . Our

33:44

second one is really around these conversational

33:46

commands , so being able to say something

33:49

like coffee with Tim at Blue

33:51

Bottle in San Francisco at 2 pm

33:53

London time and having that calendar

33:55

event sent with the right time zone with the right location

33:57

, just with keyboard shortcuts and

34:00

conversational commands . So that's our second biggest

34:02

value proposition . And the third one is using

34:04

AI to have recommendations

34:06

around when is the best time to get something

34:08

done , what is the best way to plan your schedule

34:10

? Brain-dumping tasks into Smarty

34:12

and having Smarty AI autoschedule it

34:14

into your day or into your weeks

34:16

and so really helping you make sure

34:18

you never drop the ball . And I think that last

34:20

value proposition is really where most of our

34:22

competitors are . So there are a lot of

34:24

tools that are helping you use AI

34:27

to autoschedule your day , and that's

34:29

where our biggest competitors

34:31

are .

34:32

Okay , makes sense . How

34:34

did you tackle the

34:36

problem of trusting the AI ? I

34:38

mean , if I'm just conversing with

34:41

AI and I trust this AI , he's

34:43

going to create the right appointments , send

34:46

those to my counterparts . It's

34:48

going to be a different time zone and it's

34:50

going to do it on its own and

34:52

correctly . I would double-check

34:54

everything it's doing .

34:55

Yeah , no , of course , and that's actually one

34:58

of the biggest things that we tried

35:00

to keep in mind while building out Smarty

35:03

. So I don't know if you remember XAI

35:05

it came out before

35:08

2018 . It was this assistant

35:10

, amy . You would CC

35:12

Amy on your emails and then Amy would

35:14

just do things for you , and the problem

35:17

with that experience was exactly

35:19

what you said that you were like what

35:22

is Amy going to do ? How is Amy

35:24

going to do this ? What if Amy does

35:26

it the wrong way ? And so , really , our goal with

35:28

Smarty is not to create this black box

35:30

around how things are getting done , but instead

35:32

to give you the right

35:34

commands at the right time so you know exactly

35:37

what is being done and how it's being

35:39

done . And so , instead

35:41

of you just delegating tasks

35:43

away to Smarty , it's really taking

35:45

these workflows like switching to my calendar

35:48

app , dragging and dropping , adding this contact

35:50

to that calendar invite . Instead of doing that

35:52

at that crucial step where you

35:54

have all of these mundane workflows that you

35:56

have to do , smarty is specifically replacing

35:58

that experience with a single command

36:00

where you control everything . You control exactly

36:03

the time , you control exactly the people . So

36:05

really finding that balance between giving you the

36:07

right control versus delegating

36:10

the mundane parts of product

36:12

switching , figuring out

36:14

like how does this work , things like that ?

36:17

Okay , a hard

36:19

balance to find , but

36:22

when you find it , I really trust

36:24

it to

36:26

really free up your mind , free up your calendar

36:28

, doing stuff for you , but I'm

36:31

still yeah , I can see

36:33

that you're like I don't believe that you

36:35

can fully take away

36:37

that fear , and I think it's .

36:38

You have to try the product . But it's really

36:40

. You are in control , you trigger

36:42

the commands and you

36:45

know exactly how the command is going to

36:47

work . So that confidence , I think

36:49

, and that trust , builds up over time .

36:51

Okay , I'll have to give it a go . Then you

36:56

mentioned a couple of times you

36:58

were searching for something to work

37:00

on for the rest of your life . How

37:03

does that collides maybe

37:05

doesn't collide with the

37:07

stellar growth of AI

37:10

right now ? Will

37:12

there still be a need

37:14

for how

37:17

to put it a

37:19

tool that is deep enough in

37:21

terms of you telling it what

37:24

it should be doing and really helping it

37:26

, versus , at some point , some

37:29

AI able to discover that

37:31

on their own and basically over

37:34

patting your

37:36

tool on the right and just doing

37:38

it without somebody teaching them that ? Do

37:40

you see what I mean ?

37:41

Yes , I do , but I still think

37:43

in that scenario , there will always

37:46

be an interface that you're interacting with as

37:48

the user , and , regardless

37:50

of what the AI is doing

37:52

, there's something that you are interacting with as the user

37:54

, and I want to be part of building that platform

37:57

, that interface , whatever it is . This doesn't

37:59

have to be smarty , and so I

38:01

think one of the big things as a founder is

38:04

you'll have a lot of ideas

38:06

, but finding something that you can

38:08

really , that you're really committed to in

38:11

the long run , that's really important , and for me

38:13

, even if smarty fails this concept

38:16

, this vision of what that

38:18

interface looks like , someone is going to create

38:20

it , and if I'm not going to be doing it at smarty , then

38:22

I want to go find a competitor or

38:24

another company that's working on that same vision

38:26

and go work for them , and so that's really how

38:28

it aligns for me .

38:34

And that is awesome . It really makes a lot of sense

38:36

when you describe , or when we talked about , the

38:38

product piece and the trust piece

38:40

on top of the AI . So really

38:42

, this is something that I don't see

38:44

AI solving for us . What's

38:47

happening in the background ? Yes , maybe , but

38:49

this whole how humans or tailoring

38:52

for humans , is really a hard

38:54

nut to crack , and this I don't expect

38:56

the UI to crack that in

38:58

the near future . So that's where your

39:00

tool or maybe another , as you're saying really

39:04

has to shine and

39:06

come into play .

39:08

I definitely think it's . We're really early

39:10

, we're not sure what that's gonna look like

39:12

, but it's exciting to be part of that journey

39:14

that shapes it .

39:16

Very cool . Coming

39:18

back to your students , was

39:22

there something , some kind of piece of

39:24

advice , stuff you told them again

39:26

and again to help them kickstart

39:28

their career , start on the right track

39:30

and maybe

39:33

get a glimpse on what you were doing or

39:35

something else ? Is there such such an advice

39:37

?

39:38

Yeah , it's a great question . It's actually something I've been thinking

39:40

about a lot recently , especially

39:43

with the rapid

39:46

buildup of AI tools that are coming out there

39:48

. I think AI literacy is something that is becoming

39:50

more and more important than ever before

39:52

, and that doesn't mean understanding

39:54

how AI works behind

39:57

the scenes . It's about understanding how

39:59

to use AI as a tool to

40:01

improve your own job , whatever you are doing

40:03

, and it's something that I am

40:06

telling folks today who are interested . Ai

40:08

is in such an early stage

40:11

that the next five , ten years are really

40:13

going to tell us what that industry is going

40:15

to look like , and so the more AI literacy

40:17

that you can build up today , the better , and I think

40:19

the best way to do that is by following

40:21

your passions , your hobbies , and so you said you were working

40:23

with mid-journey . If you're an artist

40:26

, if you like to draw , if you like creating art , then

40:28

I think mid-journey is like such a great tool to

40:30

start playing around with your own art and also

40:32

seeing how it responds to art , and I

40:34

think , ai literacy . In order to develop

40:36

that . The best way to do it is to figure out what are your hobbies

40:39

, what are your passions . If you like writing

40:41

, play around with chat , tbt or other

40:43

writing language , large language models , if you like

40:45

composing music or if you like paying music

40:47

, play around with an AI tool in the music scene

40:49

and understand how to prompt it , how to use

40:51

it to create something new . Because I think

40:53

as you learn those skills , you'll

40:56

be able to become an expert . Because

40:58

anyone today can become an expert in AI

41:00

because it's just so new , so early , and

41:03

the more time you invest in it today , the

41:05

better you'll be . And the best way to invest time is to

41:07

by doing it through a hobby or something that you're

41:09

passionate about . I think that's the same advice

41:11

I would have given my students 10 years ago

41:13

in these classes . If you're interested

41:15

in technology , technology can be applied to

41:18

any space , to any industry . Even back

41:20

then , if you were interested in music

41:22

, you could try to build a piano using

41:24

software . You could try to build I

41:27

don't know like a drawing tool or an art

41:29

tool using software . I think

41:31

there is something really powerful

41:35

about being able to align your passions

41:37

with your interests

41:39

and your goals and your learning

41:42

skills , because the more you can tie in something you're

41:44

trying to learn to something that you enjoy doing , the

41:46

faster and more fun I'll be .

41:48

Amen to that and I love that your answer

41:51

digs into exploration

41:53

again , saying hey , do

41:55

something with it and try what

41:57

happens . And this is exactly the same discourse

42:00

you had at the beginning of the show , talking

42:03

about how you went at your life . So

42:05

it's all full circles .

42:07

I think life , you

42:10

know yellow , you only live once . So

42:12

you need to explore everything

42:14

and figure out what is what brings

42:17

true to you .

42:18

Then go explore Fantastic

42:23

. Where would be the best place to

42:25

continue the discussion with you ?

42:27

Please find me on LinkedIn . I'm Denzil

42:29

Eden and I love

42:31

talking to people about their

42:33

careers , their journeys , their interest

42:36

in technology , ai , literacy , and I'd

42:38

love to give anyone a personalized onboarding onto

42:40

Smarty , and then you can always try out Smarty at

42:42

wwwsmartyai

42:44

. We're an early product , we have

42:47

some customers and we're always looking

42:49

for more people to give us feedback .

42:51

Then you heard her let's go there , anything

42:55

else .

42:56

No , that's it . That's me in a nutshell .

42:58

Fantastic , denzil , it was really

43:00

fun . Thank you so much for sharing your life and for

43:02

the good love we had . I had

43:04

a fun four times I had fun too .

43:05

thank you so much for having me .

43:07

Like was , and this has been another episode

43:10

of Devil's Journey . It was each other next

43:12

week . Bye , bye . Thanks

43:14

a lot for tuning in . I hope

43:16

you have enjoyed this week's episode . If

43:19

you like the show , please share , rate

43:21

and review . It helps more

43:24

listeners discover those stories

43:26

. You can find the links to all

43:28

the platforms the show appears on on

43:30

our website devjourneyinfo

43:33

slash subscribe

43:35

. Talk

43:38

to you soon .